
*****************************
** Study 3 - February 2023 **
***** Analyses do file ******
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 3 data.dta", clear

** Descriptive statistics
sum CT_scale

* Voting group variable
fre vote_22
gen voting_group=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace voting_group=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 
replace voting_group=3 if vote_22==9 | vote_22==12
replace voting_group=4 if vote_22==14
replace voting_group=5 if vote_22==15 | vote_22==16 
label var voting_group "Voting groups - second version"
label define vote_group_lab2 1 "The 'Netanyahu bloc'" 2 "The 'change bloc'" ///
							3 "Joint List" 4 "Other parties" 5 "Don't know/Didn't vote" 
label values voting_group vote_group_lab2
tab voting_group
tab vote_22 voting_group


* Creating another "age_group" item
drop age_group
recode Age (18/29=1) (30/44=2) (45/59=3) (60/99=4), gen (age_group)
label define age_lab4 1 "18-29" 2 "30-44" 3 "45-59" 4 "60+"
label value age_group age_lab4
tab age_group
order age_group, after (Age)

* Rescaling 0-1 the values in the 'religiosity_all' item
fre religiosity_all
gen religiosity_all_01=(religiosity_all-1)/3
sum religiosity_all_01

* Ideological blocs - with "other"
recode ideology (1/3=1) (4=2) (5/7=3) (8=4), gen(ideo_bloc2)
label var ideo_bloc2 "Ideological 'self-placement blocs' - with 'Other'"
label define ideo_bloc_lab2 1 "Right" 2 "Center" 3 "Left" 4 "Other"
label values ideo_bloc2 ideo_bloc_lab2
tab ideology ideo_bloc2 


*** Beliefs in "partisan/ideological" conspiracy theories ***
tab1 CON_SHIN_BET_KILLED_RABIN CON_NETANYAHU_LEGEL_PROSECUT CON_BIBI_SARA_CONTRACT
recode CON_SHIN_BET_KILLED_RABIN (1/3=0)(4/5=1)(6=0), gen(CTI_SB_KILLED_RABIN_2)
tab CON_SHIN_BET_KILLED_RABIN CTI_SB_KILLED_RABIN_2
recode CON_NETANYAHU_LEGEL_PROSECUT (1/3=0)(4/5=1)(6=0), gen(CTI_NETAN_PROSECUT_2)
tab CON_NETANYAHU_LEGEL_PROSECUT CTI_NETAN_PROSECUT_2
recode CON_BIBI_SARA_CONTRACT (1/3=0)(4/5=1)(6=0), gen(CTI_BIBI_SARA_CONTRACT_2)
tab CON_BIBI_SARA_CONTRACT CTI_BIBI_SARA_CONTRACT_2

label define ct_agree 0 "Disagree/Neutral/DK" 1 "Agree"
label values CTI_SB_KILLED_RABIN_2 ct_agree
label values CTI_NETAN_PROSECUT_2 ct_agree
label values CTI_BIBI_SARA_CONTRACT_2 ct_agree
tab1 CTI_SB_KILLED_RABIN_2-CTI_BIBI_SARA_CONTRACT_2 

*** Beliefs in "non-partisan/ideological" conspiracy theories ***
tab1 CON_VACCINE_DANGERS_HIDDEN CON_COVID_CREATED_CONSPIRACY
recode CON_VACCINE_DANGERS_HIDDEN (1/3=0)(4/5=1)(6=0), gen(CTI_VACCINE_DANGERS_2)
tab CON_VACCINE_DANGERS_HIDDEN CTI_VACCINE_DANGERS_2
recode CON_COVID_CREATED_CONSPIRACY (1/3=0)(4/5=1)(6=0), gen(CTI_COVID_CONSPIRACY_2)
tab CON_COVID_CREATED_CONSPIRACY CTI_COVID_CONSPIRACY_2
label values CTI_VACCINE_DANGERS_2 ct_agree
label values CTI_COVID_CONSPIRACY_2 ct_agree
tab1 CTI_VACCINE_DANGERS_2 CTI_COVID_CONSPIRACY_2 


** RESHAPE of the data - from Wide to Long
* Conspiracy theory number
*reshape long CON_, i(id) j(CTI_num) string
reshape long CTI_, i(id) j(CTI_string) string
order CTI_string, after(CTI_)
gen CTI_num=1 if CTI_string=="SB_KILLED_RABIN_2"
replace CTI_num=2 if CTI_string=="NETAN_PROSECUT_2"
replace CTI_num=3 if CTI_string=="BIBI_SARA_CONTRACT_2"
replace CTI_num=4 if CTI_string=="VACCINE_DANGERS_2"
replace CTI_num=5 if CTI_string=="COVID_CONSPIRACY_2"
label var CTI_num "Conspiracy theory number"
label define CTI_num_lab 1 "SB KILLED RABIN" 2 "NETANYAHU PROSECUTION" ///
						 3 "BIBI-SARA CONTRACT" 4 "VACCINE DANGERS HIDDEN" ///
						 5 "COVID-19 CONSPIRACY"
label values CTI_num CTI_num_lab
fre CTI_num


** "Belief in "partisan" conspiracy theory for the coalition **
gen POL_CT=CTI_ if CTI_num>=1 & CTI_num<=3
tab POL_CT
tab POL_CT CTI_num if coalition==1, chi col
tab POL_CT CTI_num if coalition==0, chi col

** "Belief in "non-partisan" conspiracy theory for the coalition **
gen NON_POL_CT=CTI_ if CTI_num>=4 & CTI_num<=5
tab NON_POL_CT
tab NON_POL_CT CTI_num if coalition==1, chi col
tab NON_POL_CT CTI_num if coalition==0, chi col


* "Congenial bloc" dummy
gen congenial_bloc=1 if CTI_num==1 & voting_group==1
replace congenial_bloc=0 if CTI_num==1 & voting_group==2
replace congenial_bloc=1 if CTI_num==2 & voting_group==1
replace congenial_bloc=0 if CTI_num==2 & voting_group==2
replace congenial_bloc=1 if CTI_num==3 & voting_group==2
replace congenial_bloc=0 if CTI_num==3 & voting_group==1
label var congenial_bloc "Congenial bloc"
label define cong_lab 0 "Uncongenial CT" 1 "Congenial CT"
label values congenial_bloc cong_lab
tab congenial_bloc CTI_num if voting_group==1
tab congenial_bloc CTI_num if voting_group==2


* Table 2 - "Partisan" CTs analyses in Israel
reg POL_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using Table_2.doc, replace se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) ///
keep(c.CT_scale##i.congenial_bloc) ctitle ("Study 3 - Feb. 2023") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 2. Predicting belief in partisan conspiracy theories - Israel studies") 

* Post-hoc power analysis:
retrodesign .14081, se(.0542287) alpha(0.05) /*Power=.738*/

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg POL_CT CT_scale congenial_bloc inter  i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


* Table 3 - "Non-partisan" CT analyses in the US/Israel
reg NON_POL_CT c.CT_scale##ib2.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num>3, cluster(id)
outreg2 using Table_3.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) keep(c.CT_scale##ib2.voting_group) ///
ctitle ("Study 3 - Feb. 2023, Israel") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 3. Predicting belief in non-partisan conspiracy theories - US/Israel studies") 

* Post-hoc power analysis:
retrodesign .0293462, se(.0825384) alpha(0.05) /*Power=.065*/

* Calculating the coef. of the CT scale among those in the "Netanyahu bloc"
gen net_bloc=2-voting_group if voting_group<3 
gen inter=CT_scale*net_bloc
reg NON_POL_CT CT_scale voting_group inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num>3, cluster(id)
lincom CT_scale+inter
drop inter


** Predicting specific "partisan" conspiracy theories **

* 1st item: Shin Bet Killed Rabin
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==1, r /*p=.016, in the expected direction*/

* 2nd item: The indictment against Netanyahu is due to legal prosecution
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==2, r  /*p=.319, in the expected direction*/

* 3rd item: The Netanyahus have a secret contract
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==3, r /*p=.043, in the expected direction*/

/* 
In total, all 3 interactions in the expected direction ///
2/3 statistically significant (p<.05; 1 "for" 'Netanyahu bloc' + 1 "for" ///
'change bloc'), and 1/3 insignificant (p>.1) 
*/


** Predicting specific "non-partisan" conspiracy theories **

* 1st item: The dangers of vaccines are concealed from public
reg NON_POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==4, r /*p=.426, stronger among 'Netanyahu bloc'*/

* 2nd item: COVID-19 created and intentioally distributed by powerful people
reg NON_POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==5, r /*p=.757, stronger among 'change bloc'*/

/* 
In total, 2/2 interactions insignificant (p>.1) 
*/


************************************
** Full results - Online Appendix **
************************************

* Table C2 - "Partisan" CT analyses in Israel
reg POL_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableC2.doc, replace se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 3 - Feb. 2023") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table C2. Predicting belief in partisan conspiracy theories, Israel studies - Full results") 

** Table C4 - "Non-partisan" conspiracy theory in Studies 3 & 6 **
reg NON_POL_CT c.CT_scale##ib2.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num>3, cluster(id)
outreg2 using TableC4.doc, replace se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Model 1 - Study 3") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table C4. Predicting belief in non-partisan conspiracy theories in Israel - full results") 


*********************************************
** Dropping all controls - Online Appendix **
*********************************************

* Table D2 - "Partisan" CTs analyses in Israel
reg POL_CT c.CT_scale##i.congenial_bloc i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableD2.doc, replace se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 3 - Feb. 2023") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table D2. Predicting belief in partisan conspiracy theories, Israel studies - No controls") 

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg POL_CT CT_scale congenial_bloc inter  i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter



*****************************
*** Study 4 - August 2024 ***
***** Analyses do file ******
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 4 data.dta", clear

** Descriptive statistics
sum CT_scale

* Voting group variable
fre vote_22
gen voting_group=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace voting_group=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 
replace voting_group=3 if vote_22==9 | vote_22==12
replace voting_group=4 if vote_22==14
replace voting_group=5 if vote_22==15 | vote_22==16 
label var voting_group "Voting groups - second version"
label define vote_group_lab2 1 "The 'Netanyahu bloc'" 2 "The 'change bloc'" ///
							3 "Joint List" 4 "Other parties" 5 "Don't know/Didn't vote" 
label values voting_group vote_group_lab2
tab voting_group
tab vote_22 voting_group

* Creating another "age_group" item
drop age_group
recode Age (18/29=1) (30/44=2) (45/59=3) (60/99=4), gen (age_group)
label define age_lab4 1 "18-29" 2 "30-44" 3 "45-59" 4 "60+"
label value age_group age_lab4
tab age_group
order age_group, after (Age)

* Rescaling 0-1 the values in the 'religiosity_all' item
fre religiosity_all
gen religiosity_all_01=(religiosity_all-1)/3
sum religiosity_all_01

* Ideological blocs - with "other"
recode ideology (1/3=1) (4=2) (5/7=3) (8=4), gen(ideo_bloc2)
label var ideo_bloc2 "Ideological 'self-placement blocs' - with 'Other'"
label define ideo_bloc_lab2 1 "Right" 2 "Center" 3 "Left" 4 "Other"
label values ideo_bloc2 ideo_bloc_lab2
tab ideology ideo_bloc2 


*** Beliefs in "partisan/ideological" conspiracy theories ***

tab1 HID_ATTACK_NETANYAHU NETANYAHU_PROLONGS_WAR
recode HID_ATTACK_NETANYAHU (1/3=0)(4/5=1)(6=0), gen(CTI_HID_ATTACK_NETANYAHU)
tab HID_ATTACK_NETANYAHU CTI_HID_ATTACK_NETANYAHU
recode NETANYAHU_PROLONGS_WAR (1/3=0)(4/5=1)(6=0), gen(CTI_NETANYAHU_PROLONGS_WAR)
tab NETANYAHU_PROLONGS_WAR CTI_NETANYAHU_PROLONGS_WAR
label define ct_agree 0 "Disagree/Neutral/DK" 1 "Agree"
label values CTI_HID_ATTACK_NETANYAHU ct_agree
label values CTI_NETANYAHU_PROLONGS_WAR ct_agree
tab1 CTI_HID_ATTACK_NETANYAHU CTI_NETANYAHU_PROLONGS_WAR 

** RESHAPE of the data - from Wide to Long
rename HID_ATTACK_NETANYAHU CON_HID_ATTACK_NETANYAHU
rename NETANYAHU_PROLONGS_WAR CON_NETANYAHU_PROLONGS_WAR

* Conspiracy theory number
*reshape long CON_, i(id) j(CTI_num) string
reshape long CTI_, i(id) j(CTI_string) string
order CTI_string, after(CTI_)
fre CTI_string
gen CTI_num=1 if CTI_string=="HID_ATTACK_NETANYAHU"
replace CTI_num=2 if CTI_string=="NETANYAHU_PROLONGS_WAR"
label var CTI_num "Conspiracy theory number"
label define CTI_num_lab 1 "HID ATTACK NETANYAHU" 2 "NETANYAHU PROLONGS WAR"
label values CTI_num CTI_num_lab
fre CTI_num

* The DV: Belief in the CT
rename CTI_ belief_CT
tab belief_CT
tab belief_CT CTI_num if voting_group==1, chi col
tab belief_CT CTI_num if voting_group==2, chi col


* "Congenial bloc" dummy
fre CTI_num
gen congenial_bloc=1 if CTI_num==1 & voting_group==1
replace congenial_bloc=0 if CTI_num==1 & voting_group==2
replace congenial_bloc=1 if CTI_num==2 & voting_group==2
replace congenial_bloc=0 if CTI_num==2 & voting_group==1
label var congenial_bloc "Congenial bloc"
label define cong_lab 0 "Uncongenial CT" 1 "Congenial CT"
label values congenial_bloc cong_lab
tab congenial_bloc CTI_num if voting_group==1
tab congenial_bloc CTI_num if voting_group==2


* Combined "partisan" CTs analyses
reg belief_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using Table_2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) ///
keep(c.CT_scale##i.congenial_bloc) ctitle ("Study 4 - Aug. 2024") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 2. Predicting belief in partisan conspiracy theories - Israel studies") 

* Post-hoc power analysis:
retrodesign .1784339, se(.07289) alpha(0.05) /*Power=.687*/

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg belief_CT CT_scale congenial_bloc inter  i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


** Predicting specific "partisan" conspiracy theories **

* 1st item: Top security officials hid the 7/10 attack from Netanyahu to hurt him
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==1, r /*p=.005, in the expected direction*/

* 2nd item: NETANYAHU_PROLONGS_WAR
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==2, r /*p=.410, in the expected direction*/

/* 
In total, all 2 interactions in the expected direction ///
1/2 statistically significant (p<.05; "for" 'Netanyahu bloc', and 1/2 insignificant (p>.1) and in the expected direction
*/


******************************************
** Full results for the Online Appendix **
******************************************
* Table C2 - "Partisan" CTs analyses in Israel
reg belief_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableC2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 4 - Aug. 2024") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table C2. Predicting belief in partisan conspiracy theories, Israel studies - Full results") 


*********************************************
** Dropping all controls - Online Appendix **
*********************************************

* Table D2 - "Partisan" CT analyses in Israel
reg belief_CT c.CT_scale##i.congenial_bloc i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableD2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 4 - Aug. 2024") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table D2. Predicting belief in partisan conspiracy theories, Israel studies - No controls") 

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg belief_CT CT_scale congenial_bloc inter i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter




*****************************
** Study 5 - December2024 ***
***** Analyses do file ******
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 5 data.dta", clear


** Descriptive statistics
sum CT_scale

* Voting group variable
fre vote_22
gen voting_group=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace voting_group=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 
replace voting_group=3 if vote_22==9 | vote_22==12
replace voting_group=4 if vote_22==14
replace voting_group=5 if vote_22==15 | vote_22==16 
label var voting_group "Voting groups - second version"
label define vote_group_lab2 1 "The 'Netanyahu bloc'" 2 "The 'change bloc'" ///
							3 "Joint List" 4 "Other parties" 5 "Don't know/Didn't vote" 
label values voting_group vote_group_lab2
tab voting_group
tab vote_22 voting_group


* Creating another "age_group" item
drop age_group
recode Age (18/29=1) (30/44=2) (45/59=3) (60/99=4), gen (age_group)
label define age_lab4 1 "18-29" 2 "30-44" 3 "45-59" 4 "60+"
label value age_group age_lab4
tab age_group
order age_group, after (Age)

* Recoding the values in the 'religiosity_all' item
fre religiosity_all
gen religiosity_all_01=(religiosity_all-1)/3
sum religiosity_all_01

* Ideological blocs - with "other"
recode ideology (1/3=1) (4=2) (5/7=3) (8=4), gen(ideo_bloc2)
label var ideo_bloc2 "Ideological 'self-placement blocs' - with 'Other'"
label define ideo_bloc_lab2 1 "Right" 2 "Center" 3 "Left" 4 "Other"
label values ideo_bloc2 ideo_bloc_lab2
tab ideology ideo_bloc2 


*** Beliefs in "partisan/ideological" conspiracy theories ***
*tab1 HID_ATTACK_NETANYAHU IDF_HID_PM_HAMAS_INFO PM_ASSOC_LEAKED_INFO FELDSTEIN_POL_ARREST
recode HID_ATTACK_NETANYAHU (1/3=0)(4/5=1)(6=0), gen(CTI_HID_ATTACK_NETANYAHU)
tab HID_ATTACK_NETANYAHU CTI_HID_ATTACK_NETANYAHU
recode IDF_HID_PM_HAMAS_INFO (1/3=0)(4/5=1)(6=0), gen(CTI_IDF_HID_PM_HAMAS_INFO)
tab IDF_HID_PM_HAMAS_INFO CTI_IDF_HID_PM_HAMAS_INFO
recode PM_ASSOC_LEAKED_INFO (1/3=0)(4/5=1)(6=0), gen(CTI_PM_ASSOC_LEAKED_INFO)
tab PM_ASSOC_LEAKED_INFO CTI_PM_ASSOC_LEAKED_INFO
recode FELDSTEIN_POL_ARREST (1/3=0)(4/5=1)(6=0), gen(CTI_FELDSTEIN_POL_ARREST)
tab FELDSTEIN_POL_ARREST CTI_FELDSTEIN_POL_ARREST

label define ct_agree 0 "Disagree/Neutral/DK" 1 "Agree"
label values CTI_HID_ATTACK_NETANYAHU ct_agree
label values CTI_IDF_HID_PM_HAMAS_INFO ct_agree
label values CTI_PM_ASSOC_LEAKED_INFO ct_agree
label values CTI_FELDSTEIN_POL_ARREST ct_agree
tab1 CTI_HID_ATTACK_NETANYAHU-CTI_FELDSTEIN_POL_ARREST


recode NETANYAHU_PROLONGS_WAR (1/3=0)(4/5=1)(6=0), gen(CTI_NETANYAHU_PROLONGS_WAR)
tab NETANYAHU_PROLONGS_WAR CTI_NETANYAHU_PROLONGS_WAR
label values CTI_NETANYAHU_PROLONGS_WAR ct_agree
tab1 CTI_NETANYAHU_PROLONGS_WAR 


** RESHAPE of the data - from Wide to Long
rename HID_ATTACK_NETANYAHU CON_HID_ATTACK_NETANYAHU
rename IDF_HID_PM_HAMAS_INFO CON_IDF_HID_PM_HAMAS_INFO
rename PM_ASSOC_LEAKED_INFO CON_PM_ASSOC_LEAKED_INFO
rename FELDSTEIN_POL_ARREST CON_FELDSTEIN_POL_ARREST
rename NETANYAHU_PROLONGS_WAR CON_NETANYAHU_PROLONGS_WAR

* Conspiracy theory number
*reshape long CON_, i(id) j(CTI_num) string
reshape long CTI_, i(id) j(CTI_string) string
order CTI_string, after(CTI_)
fre CTI_string
gen CTI_num=1 if CTI_string=="HID_ATTACK_NETANYAHU"
replace CTI_num=2 if CTI_string=="IDF_HID_PM_HAMAS_INFO"
replace CTI_num=3 if CTI_string=="PM_ASSOC_LEAKED_INFO"
replace CTI_num=4 if CTI_string=="FELDSTEIN_POL_ARREST"
replace CTI_num=5 if CTI_string=="NETANYAHU_PROLONGS_WAR"
label var CTI_num "Conspiracy theory number"
label define CTI_num_lab 1 "HID ATTACK NETANYAHU" 2 "IDF HID PM HAMAS INFO" ///
						 3 "PM ASSOC LEAKED INFO" 4 "FELDSTEIN POL ARREST" ///
						 5 "NETANYAHU PROLONGS WAR"
label values CTI_num CTI_num_lab
fre CTI_num


* The DV: Belief in the CT
rename CTI_ belief_CT
tab belief_CT
tab belief_CT CTI_num if voting_group==1, chi col
tab belief_CT CTI_num if voting_group==2, chi col


* "Congenial bloc" dummy
fre CTI_num
gen congenial_bloc=1 if CTI_num==1 & voting_group==1
replace congenial_bloc=0 if CTI_num==1 & voting_group==2
replace congenial_bloc=1 if CTI_num==2 & voting_group==1
replace congenial_bloc=0 if CTI_num==2 & voting_group==2
replace congenial_bloc=1 if CTI_num==3 & voting_group==2
replace congenial_bloc=0 if CTI_num==3 & voting_group==1
replace congenial_bloc=1 if CTI_num==4 & voting_group==1
replace congenial_bloc=0 if CTI_num==4 & voting_group==2
replace congenial_bloc=1 if CTI_num==5 & voting_group==2
replace congenial_bloc=0 if CTI_num==5 & voting_group==1
label var congenial_bloc "Congenial bloc"
label define cong_lab 0 "Uncongenial CT" 1 "Congenial CT"
label values congenial_bloc cong_lab
tab congenial_bloc CTI_num if voting_group==1
tab congenial_bloc CTI_num if voting_group==2


* Combined "partisan" CTs analyses
reg belief_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using Table_2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) ///
keep(c.CT_scale##i.congenial_bloc) ctitle ("Study 5 - Dec. 2024") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 2. Predicting belief in partisan conspiracy theories - Israel studies") 

* Post-hoc power analysis:
retrodesign .1659753, se(.0682946) alpha(0.05) /*Power=.681*/

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg belief_CT CT_scale congenial_bloc inter  i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


** Predicting specific "partisan" conspiracy theories **
fre CTI_num

* 1st item: Top security officials hid the 7/10 attack from Netanyahu to hurt him
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==1, r /*p=.052, in the expected direction*/

* 2nd item: Senior IDF personal deliberately hid from ///
* the PM important information re: Hamas that was collected during the war in Gaza
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==2, r /*p=.137, in the expected direction*/ 

* 3rd item: Close associates of the PM deliberately ///
* leaked secret documents to non-Israeli sources to prevent a hostage-releasing deal
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==3, r /*p=.048, in the expected direction*/

* 4th item: The arrest and investigation of Eli Feldstein, ///
* who worked at PM's office, were done out of political reasons and to harm the PM
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==4, r /*p=.493, in the UNEXPECTED direction*/

* 5th item: NETANYAHU_PROLONGS_WAR
reg belief_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==5, r /*p=.580, in the expected direction*/

/* 
In total, 4/5 interactions in the expected direction ///
1/5 statistically significant (p<.05; "for" 'change bloc'), 1/5 'marginally' ///
significant (p<.1; "for 'Netanyahu bloc') and 3/5 insignificant (p>.1), two in the expected direction and one in the unexpected direction
*/


******************************************
** Full results for the Online Appendix **
******************************************

* Table C2 - "Partisan" CT analyses in Israel
reg belief_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableC2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 5 - Dec. 2024") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table C2. Predicting belief in partisan conspiracy theories, Israel studies - Full results") 


*********************************************
** Dropping all controls - Online Appendix **
*********************************************

* Table D2 - "Partisan" CTs analyses in Israel
reg belief_CT c.CT_scale##i.congenial_bloc i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableD2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 5 - Dec. 2024") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table D2. Predicting belief in partisan conspiracy theories, Israel studies - No controls") 

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg belief_CT CT_scale congenial_bloc inter i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


********************************************
** "Jackknife" analysis - Online Appendix **
********************************************

** Running the main analysis, each time dropping 1 "partisan" CT **

gen inter=CT_scale*congenial_bloc

* Without the 1st "partisan/ideological" CT
reg belief_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1, cluster(id) /*b=.136; p=.061*/
scalar b1 = _b[inter]
scalar p1 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=1: Coef=" %6.3f b1 "   p=" %6.3f p1

* Without the 2nd "partisan/ideological" CT
reg belief_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2, cluster(id) /*b=.149; p=.028*/
scalar b2 = _b[inter]
scalar p2 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 3rd "partisan/ideological" CT
reg belief_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=3, cluster(id) /*b=.154; p=.036*/
scalar b3 = _b[inter]
scalar p3 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 4th "partisan/ideological" CT
reg belief_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=4, cluster(id) /*b=.199; p=.005*/
scalar b4 = _b[inter]
scalar p4 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 5th "partisan/ideological" CT
reg belief_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=5, cluster(id) /*b=.183; p=.019*/
scalar b5 = _b[inter]
scalar p5 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

gen b_inter=.
gen p_inter=.
replace b_inter=b1 in 1
replace b_inter=b2 in 2
replace b_inter=b3 in 3
replace b_inter=b4 in 4
replace b_inter=b5 in 5
replace p_inter=p1 in 1
replace p_inter=p2 in 2
replace p_inter=p3 in 3
replace p_inter=p4 in 4
replace p_inter=p5 in 5

*drop inter

* A histogram of the 'jackknife' coefficients
twoway hist b_inter, bin(8) xscale(range(0 .25)) ///
xlabel(0(.05).25, labsize(medium)) scheme(s2mono) legend(off) ///
yscale(range(0 30)) ylabel(0(5)30, angle(0) labsize(medium)) ///
graphregion(fcolor(white)) plotregion(margin(5 5 2 2)) /// 
xtitle("The interaction coefficient", size(medium)) ///
title(" ", size(medium))
/* || kdensity b_inter */
/* title("Study 5 estimates: Each time dropping one conspiracy theory") */

sum b_inter p_inter
drop b_inter p_inter



*****************************
**** Study 6 - April 2025 ***
***** Analyses do file ******
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 6 data.dta", clear


** Descriptive statistics
sum CT_scale

* Voting group variable
fre vote_22
gen voting_group=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace voting_group=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 
replace voting_group=3 if vote_22==9 | vote_22==12
replace voting_group=4 if vote_22==14
replace voting_group=5 if vote_22==15 | vote_22==16 
label var voting_group "Voting groups - second version"
label define vote_group_lab2 1 "The 'Netanyahu bloc'" 2 "The 'change bloc'" ///
							3 "Joint List" 4 "Other parties" 5 "Don't know/Didn't vote" 
label values voting_group vote_group_lab2
tab voting_group
tab vote_22 voting_group


* Creating another "age_group" item
drop age_group
recode Age (18/29=1) (30/44=2) (45/59=3) (60/99=4), gen (age_group)
label define age_lab4 1 "18-29" 2 "30-44" 3 "45-59" 4 "60+"
label value age_group age_lab4
tab age_group
order age_group, after (Age)

* Rescaling 0-1 the values in the 'religiosity_all' item
fre religiosity_all
gen religiosity_all_01=(religiosity_all-1)/3
sum religiosity_all_01

* Ideological blocs - with "other"
recode ideology (1/3=1) (4=2) (5/7=3) (8=4), gen(ideo_bloc2)
label var ideo_bloc2 "Ideological 'self-placement blocs' - with 'Other'"
label define ideo_bloc_lab2 1 "Right" 2 "Center" 3 "Left" 4 "Other"
label values ideo_bloc2 ideo_bloc_lab2
tab ideology ideo_bloc2 


*** Beliefs in "partisan/ideological" conspiracy theories ***
tab1 CON_SHIN_BET_KILLED_RABIN CON_NETANYAHU_LEGEL_PROSECUT CON_BIBI_SARA_CONTRACT HID_ATTACK_NETANYAHU QATARGATE DEEPSTATE_GOV 
recode CON_SHIN_BET_KILLED_RABIN (1/3=0)(4/5=1)(6=0), gen(CTI_SB_KILLED_RABIN_2)
tab CON_SHIN_BET_KILLED_RABIN CTI_SB_KILLED_RABIN_2
recode CON_NETANYAHU_LEGEL_PROSECUT (1/3=0)(4/5=1)(6=0), gen(CTI_NETAN_PROSECUT_2)
tab CON_NETANYAHU_LEGEL_PROSECUT CTI_NETAN_PROSECUT_2
recode CON_BIBI_SARA_CONTRACT (1/3=0)(4/5=1)(6=0), gen(CTI_BIBI_SARA_CONTRACT_2)
tab CON_BIBI_SARA_CONTRACT CTI_BIBI_SARA_CONTRACT_2
recode HID_ATTACK_NETANYAHU (1/3=0)(4/5=1)(6=0), gen(CTI_HID_ATTACK_NETANYAHU_2)
tab HID_ATTACK_NETANYAHU CTI_HID_ATTACK_NETANYAHU_2
recode QATARGATE (1/3=0)(4/5=1)(6=0), gen(CTI_QATARGATE_2)
tab QATARGATE CTI_QATARGATE_2
recode DEEPSTATE_GOV (1/3=0)(4/5=1)(6=0), gen(CTI_DEEPSTATE_GOV_2)
tab DEEPSTATE_GOV CTI_DEEPSTATE_GOV_2

label define ct_agree 0 "Disagree/Neutral/DK" 1 "Agree"
label values CTI_SB_KILLED_RABIN_2 ct_agree
label values CTI_NETAN_PROSECUT_2 ct_agree
label values CTI_BIBI_SARA_CONTRACT_2 ct_agree
label values CTI_HID_ATTACK_NETANYAHU_2 ct_agree
label values CTI_QATARGATE_2 ct_agree
label values CTI_DEEPSTATE_GOV_2 ct_agree
tab1 CTI_SB_KILLED_RABIN_2-CTI_DEEPSTATE_GOV_2 

*** Beliefs in "non-partisan/ideological" conspiracy theories ***
tab1 CON_VACCINE_DANGERS_HIDDEN CON_COVID_CREATED_CONSPIRACY
recode CON_VACCINE_DANGERS_HIDDEN (1/3=0)(4/5=1)(6=0), gen(CTI_VACCINE_DANGERS_2)
tab CON_VACCINE_DANGERS_HIDDEN CTI_VACCINE_DANGERS_2
recode CON_COVID_CREATED_CONSPIRACY (1/3=0)(4/5=1)(6=0), gen(CTI_COVID_CONSPIRACY_2)
tab CON_COVID_CREATED_CONSPIRACY CTI_COVID_CONSPIRACY_2
label values CTI_VACCINE_DANGERS_2 ct_agree
label values CTI_COVID_CONSPIRACY_2 ct_agree
tab1 CTI_VACCINE_DANGERS_2 CTI_COVID_CONSPIRACY_2 


** RESHAPE of the data - from Wide to Long
* Conspiracy theory number
*reshape long CON_, i(id) j(CTI_num) string
reshape long CTI_, i(id) j(CTI_string) string
order CTI_string, after(CTI_)
gen CTI_num=1 if CTI_string=="SB_KILLED_RABIN_2"
replace CTI_num=2 if CTI_string=="NETAN_PROSECUT_2"
replace CTI_num=3 if CTI_string=="BIBI_SARA_CONTRACT_2"
replace CTI_num=4 if CTI_string=="VACCINE_DANGERS_2"
replace CTI_num=5 if CTI_string=="COVID_CONSPIRACY_2"
replace CTI_num=6 if CTI_string=="HID_ATTACK_NETANYAHU_2"
replace CTI_num=7 if CTI_string=="QATARGATE_2"
replace CTI_num=8 if CTI_string=="DEEPSTATE_GOV_2"
label var CTI_num "Conspiracy theory number"
label define CTI_num_lab 1 "SB KILLED RABIN" 2 "NETANYAHU PROSECUTION" ///
						 3 "BIBI-SARA CONTRACT" 4 "VACCINE DANGERS HIDDEN" ///
						 5 "COVID-19 CONSPIRACY" 6 "HID ATTACK NETANYAHU" ///
						 7 "QATARGATE" 8 "DEEPSTATE"
label values CTI_num CTI_num_lab
fre CTI_num

** "Belief in "partisan" conspiracy theory for the coalition **
gen POL_CT=CTI_ if CTI_num>=1 & CTI_num<=3
replace POL_CT=CTI_ if CTI_num>=6 & CTI_num<=8
tab POL_CT
tab POL_CT CTI_num if coalition==1, chi col
tab POL_CT CTI_num if coalition==0, chi col

** "Belief in "non-partisan/ideological" conspiracy theory for the coalition **
gen NON_POL_CT=CTI_ if CTI_num>=4 & CTI_num<=5
tab NON_POL_CT
tab NON_POL_CT CTI_num if coalition==1, chi col
tab NON_POL_CT CTI_num if coalition==0, chi col


* "Congenial bloc" dummy
gen congenial_bloc=1 if CTI_num==1 & voting_group==1
replace congenial_bloc=0 if CTI_num==1 & voting_group==2
replace congenial_bloc=1 if CTI_num==2 & voting_group==1
replace congenial_bloc=0 if CTI_num==2 & voting_group==2
replace congenial_bloc=1 if CTI_num==3 & voting_group==2
replace congenial_bloc=0 if CTI_num==3 & voting_group==1
replace congenial_bloc=1 if CTI_num==6 & voting_group==1
replace congenial_bloc=0 if CTI_num==6 & voting_group==2
replace congenial_bloc=1 if CTI_num==7 & voting_group==2
replace congenial_bloc=0 if CTI_num==7 & voting_group==1
replace congenial_bloc=1 if CTI_num==8 & voting_group==1
replace congenial_bloc=0 if CTI_num==8 & voting_group==2
label var congenial_bloc "Congenial bloc"
label define cong_lab 0 "Uncongenial CT" 1 "Congenial CT"
label values congenial_bloc cong_lab
tab congenial_bloc CTI_num if voting_group==1
tab congenial_bloc CTI_num if voting_group==2


* Combined "partisan" CTs analyses
reg POL_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using Table_2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) ///
keep(c.CT_scale##i.congenial_bloc) ctitle ("Study 6 - April 2025") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 2. Predicting belief in partisan conspiracy theories - Israel studies") 

* Post-hoc power analysis:
retrodesign .1741133, se(.0580118) alpha(0.05) /*Power=.851*/

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg POL_CT CT_scale congenial_bloc inter  i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


** Combined "Non-partisan" CTs analyses **
reg NON_POL_CT c.CT_scale##ib2.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & (CTI_num>=4 & CTI_num<=5), cluster(id)
outreg2 using Table_3.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) keep(c.CT_scale##ib2.voting_group) ///
ctitle ("Study 6 - April 2025, Israel") ///
addtext(CT Fixed-effects, "YES", Individual-level controls, "YES") ///
title ("Table 3. Predicting belief in non-partisan conspiracy theories - US/Israel studies") 


* Calculating the coef. of the CT scale among those in the "Netanyahu bloc"
gen net_bloc=2-voting_group if voting_group<3 
gen inter=CT_scale*net_bloc
reg NON_POL_CT CT_scale voting_group inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num>3, cluster(id)
lincom CT_scale+inter
drop inter



** Predicting specific "partisan" conspiracy theories **

* 1st item: Shin Bet Killed Rabin
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==1, r /*p=.102, in the expected direction*/

* 2nd item: The indictment against Netanyahu is due to legal prosecution
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==2, r  /*p=.060, in the expected direction*/

* 3rd item: The Netanyahus have a secret contract
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==3, r /*p=.011, in the expected direction*/

* 4st item: Top security officials hid the 7/10 attack from Netanyahu to hurt him
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==6, r  /*p=.037, in the expected direction*/

* 5st item: "Qatargate"
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==7, r  /*p=.048, in the expected direction*/

* 6st item: "Deep State"
reg POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==8, r  /*p=.172, in the expected direction*/

/* 
In total, all interactions in the expected direction ///
3/6 statistically significant (p<.05; 2 "for" 'change bloc', 1 "for 'Netanyahu bloc') 1/6 'marginally' significant (p<.1; 1 "for 'Netanyahu bloc') and 2/6 insignificant (p>.1)
*/


** Predicting specific "non-partisan" conspiracy theories **

* 1st item: The dangers of vaccines are concealed from public
reg NON_POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==4, r /*p=.079, stronger among 'change bloc'*/

* 2nd item: COVID-19 created and intentioally distributed by powerful people
reg NON_POL_CT c.CT_scale##i.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 if voting_group<3 & CTI_num==5, r /*p=.929, stronger among 'Netanyahu bloc'*/

/* 
In total, 1/2 interactions 'marginally' significant (p<.1) and 1/2 interactions insignificant (p>.1) 
*/


******************************************
** Full results for the Online Appendix **
******************************************

* Table C2 - "Partisan" CTs analyses in Israel
reg POL_CT c.CT_scale##i.congenial_bloc i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableC2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 6 - April 2025") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table C2. Predicting belief in partisan conspiracy theories, Israel studies - Full results") 

** Table C4 - "Non-partisan" CTs in Studies 3 & 6 **
reg NON_POL_CT c.CT_scale##ib2.voting_group i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num>3, cluster(id)
outreg2 using TableC4.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Model 2 - Study 6") ///
addtext(CT Fixed-effects, "YES") /// 
title ("Table C4. Predicting belief in non-partisan conspiracy theories in Israel - full results") 


*********************************************
** Dropping all controls - Online Appendix **
*********************************************

* Table D2 - "Partisan" CTs analyses in Israel
reg POL_CT c.CT_scale##i.congenial_bloc i.CTI_num if voting_group<3, cluster(id)
outreg2 using TableD2.doc, append se dec(3) alpha (.001, .01, .05) ///
symbol (***, **, *) drop(i.CTI_num) ctitle ("Study 6 - April 2025") ///
addtext(CT Fixed-effects, "YES") ///
title ("Table D2. Predicting belief in partisan conspiracy theories, Israel studies - No controls") 

* Calculating the coef. of the CT scale among those in the "congenial bloc"
gen inter=CT_scale*congenial_bloc
reg POL_CT CT_scale congenial_bloc inter i.CTI_num if voting_group<3, cluster(id)
lincom CT_scale+inter
drop inter


********************************************
** "Jackknife" analysis - Online Appendix **
********************************************

** Running the main analysis, each time dropping 1 "partisan" CT **

gen inter=CT_scale*congenial_bloc

* Without the 1st "partisan" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1, cluster(id) /*b=.182; p=.004*/
scalar b1 = _b[inter]
scalar p1 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=1: Coef=" %6.3f b1 "   p=" %6.3f p1

* Without the 2nd "partisan" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2, cluster(id) /*b=.163; p=.005*/
scalar b2 = _b[inter]
scalar p2 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 3rd "partisan" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=3, cluster(id) /*b=.157; p=.011*/
scalar b3 = _b[inter]
scalar p3 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 4th "partisan/ideological" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=6, cluster(id) /*b=.167; p=.005*/
scalar b4 = _b[inter]
scalar p4 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 5th "partisan" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=7, cluster(id) /*b=.194; p=.001*/
scalar b5 = _b[inter]
scalar p5 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 6th "partisan" CT
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=8, cluster(id) /*b=.189; p=.002*/
scalar b6 = _b[inter]
scalar p6 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))


gen b_inter=.
gen p_inter=.
replace b_inter=b1 in 1
replace b_inter=b2 in 2
replace b_inter=b3 in 3
replace b_inter=b4 in 4
replace b_inter=b5 in 5
replace b_inter=b6 in 6
replace p_inter=p1 in 1
replace p_inter=p2 in 2
replace p_inter=p3 in 3
replace p_inter=p4 in 4
replace p_inter=p5 in 5
replace p_inter=p6 in 6

*drop inter

* A histogram of the 'jackknife' coefficients
twoway hist b_inter, bin(8) xscale(range(0 .25)) ///
xlabel(0(.05).25, labsize(medium)) scheme(s2mono) legend(off) ///
yscale(range(0 40)) ylabel(0(10)40, angle(0) labsize(medium)) ///
graphregion(fcolor(white)) plotregion(margin(5 5 2 2)) /// 
xtitle("The interaction coefficient", size(medium)) ///
title(" ", size(medium))
/* || kdensity b_inter */
/* title("Study 6 estimates: Each time dropping one conspiracy theory") */

sum b_inter p_inter
drop b_inter p_inter


** Running the main analysis, each time dropping 2 "partisan" CTs **

* Without the 1st and 2nd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1 & CTI_num!=2, cluster(id) /*b=.169; p=.008*/
scalar b1 = _b[inter]
scalar p1 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=1&2: Coef=" %6.3f b1 "   p=" %6.3f p1

* Without the 1st and 3rd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1 & CTI_num!=3, cluster(id) /*b=.160; p=.017*/
scalar b2 = _b[inter]
scalar p2 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=1&3: Coef=" %6.3f b2 "   p=" %6.3f p2

* Without the 1st and 4rd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1 & CTI_num!=6, cluster(id) 
scalar b3 = _b[inter]
scalar p3 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 1st and 5rd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1 & CTI_num!=7, cluster(id) 
scalar b4 = _b[inter]
scalar p4 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 1st and 6rd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=1 & CTI_num!=8, cluster(id) 
scalar b5 = _b[inter]
scalar p5 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 2nd and 3rd "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2 & CTI_num!=3, cluster(id) /*b=.142; p=.024*/
scalar b6 = _b[inter]
scalar p6 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=2&3: Coef=" %6.3f b6 "   p=" %6.3f p6

* Without the 2nd and 4th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2 & CTI_num!=6, cluster(id) 
scalar b7 = _b[inter]
scalar p7 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 2nd and 5th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2 & CTI_num!=7, cluster(id) 
scalar b8 = _b[inter]
scalar p8 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 2nd and 6th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=2 & CTI_num!=8, cluster(id) 
scalar b9 = _b[inter]
scalar p9 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 3rd and 4th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=3 & CTI_num!=6, cluster(id) /*b=.142; p=.024*/
scalar b10 = _b[inter]
scalar p10 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=3&4: Coef=" %6.3f b10 "   p=" %6.3f p10

* Without the 3rd and 5th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=3 & CTI_num!=7, cluster(id)
scalar b11 = _b[inter]
scalar p11 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 3rd and 6th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=3 & CTI_num!=8, cluster(id)
scalar b12 = _b[inter]
scalar p12 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 4th and 5th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=6 & CTI_num!=7, cluster(id) /*b=.186; p=.002*/
scalar b13 = _b[inter]
scalar p13 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=4&5: Coef=" %6.3f b13 "   p=" %6.3f p13

* Without the 4th and 6th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=6 & CTI_num!=8, cluster(id)
scalar b14 = _b[inter]
scalar p14 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))

* Without the 5th and 6th "partisan" CTs
reg POL_CT CT_scale i.congenial_bloc inter i.ideo_bloc2 i.age_group i.jewish i.gender college_educ religiosity_all_01 i.CTI_num if voting_group<3 & CTI_num!=7 & CTI_num!=8, cluster(id) /*b=.209; p=.001*/
scalar b15 = _b[inter]
scalar p15 = 2 * ttail(e(df_r), abs(_b[inter]/_se[inter]))
di "CTI_num!=5&6: Coef=" %6.3f b15 "   p=" %6.3f p15


gen b_inter=.
gen p_inter=.
replace b_inter=b1 in 1
replace b_inter=b2 in 2
replace b_inter=b3 in 3
replace b_inter=b4 in 4
replace b_inter=b5 in 5
replace b_inter=b6 in 6
replace b_inter=b7 in 7
replace b_inter=b8 in 8
replace b_inter=b9 in 9
replace b_inter=b10 in 10
replace b_inter=b11 in 11
replace b_inter=b12 in 12
replace b_inter=b13 in 13
replace b_inter=b14 in 14
replace b_inter=b15 in 15

replace p_inter=p1 in 1
replace p_inter=p2 in 2
replace p_inter=p3 in 3
replace p_inter=p4 in 4
replace p_inter=p5 in 5
replace p_inter=p6 in 6
replace p_inter=p7 in 7
replace p_inter=p8 in 8
replace p_inter=p9 in 9
replace p_inter=p10 in 10
replace p_inter=p11 in 11
replace p_inter=p12 in 12
replace p_inter=p13 in 13
replace p_inter=p14 in 14
replace p_inter=p15 in 15

*drop inter


* A histogram of the 'jackknife' coefficients
twoway hist b_inter, bin(8) xscale(range(0 .25)) ///
xlabel(0(.05).25, labsize(medium)) scheme(s2mono) legend(off) ///
yscale(range(0 25)) ylabel(0(5)25, angle(0) labsize(medium)) ///
graphregion(fcolor(white)) plotregion(margin(5 5 2 2)) /// 
xtitle("The interaction coefficient", size(medium)) ///
title("Study 6 estimates: Each time dropping two conspiracy theories", size(medium))
/* || kdensity b_inter */


sum b_inter p_inter
drop b_inter p_inter






****************************************************
** Descriptive statistics for the Online Appendix **
****************************************************

*****************************
** Study 3 - February 2023 **
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 3 data.dta", clear


* Age group
drop age_group
recode Age (18/29=1) (30/49=2) (50/69=3) (70/99=4), gen (age_group)
label define ageg2_lab 1 "18-29" 2 "30-49" 3 "50-69" 4 "70+"
label value age_group ageg2_lab
tab Age age_group
tab age_group

* Gender
tab gender

* Jewish
tab jewish

* College education
tab college_educ

* Religiosity
tab religiosity_all if jewish==1 

* Coalition
drop coalition_23
tab vote_22
gen coalition_23=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace coalition_23=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 | vote_22==9 ///
						   | vote_22==12
replace coalition_23=3 if vote_22>=14 & vote_22<=16 
label define coal_lab1 1 "Coalition" 2 "Opposition" 3 "Other"
label values coalition_23 coal_lab1
tab vote_22 coalition_23
tab coalition_23 

* Ideological "blocs"
tab ideology
recode ideology (1/3=1) (4=2) (5/7=3) (8/100=4), gen(ideo_bloc)
label define blocs_lab1 1 "Right" 2 "Center" 3 "Left" 4 "Other" 
label values ideo_bloc blocs_lab1
tab ideology ideo_bloc
tab ideo_bloc


***************************
** Study 4 - August 2024 **
***************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 4 data.dta", clear

* Age group
drop age_group
recode Age (18/29=1) (30/49=2) (50/69=3) (70/99=4), gen (age_group)
label define ageg2_lab 1 "18-29" 2 "30-49" 3 "50-69" 4 "70+"
label value age_group ageg2_lab
tab Age age_group
tab age_group

* Gender
tab gender

* Jewish
tab jewish

* College education
tab college_educ

* Religiosity
tab religiosity_all if jewish==1 

* Coalition
drop coalition_23
tab vote_22
gen coalition_23=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace coalition_23=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 | vote_22==9 ///
						   | vote_22==12
replace coalition_23=3 if vote_22>=14 & vote_22<=16 
label define coal_lab1 1 "Coalition" 2 "Opposition" 3 "Other"
label values coalition_23 coal_lab1
tab vote_22 coalition_23
tab coalition_23 

* Ideological "blocs"
tab ideology
recode ideology (1/3=1) (4=2) (5/7=3) (8/100=4), gen(ideo_bloc)
label define blocs_lab1 1 "Right" 2 "Center" 3 "Left" 4 "Other" 
label values ideo_bloc blocs_lab1
tab ideology ideo_bloc
tab ideo_bloc


*****************************
** Study 5 - December 2024 **
*****************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 5 data.dta", clear


* Age group
drop age_group
recode Age (18/29=1) (30/49=2) (50/69=3) (70/99=4), gen (age_group)
label define ageg2_lab 1 "18-29" 2 "30-49" 3 "50-69" 4 "70+"
label value age_group ageg2_lab
tab Age age_group
tab age_group

* Gender
tab gender

* Jewish
tab jewish

* College education
tab college_educ

* Religiosity
tab religiosity_all if jewish==1 

* Coalition
drop coalition_23
tab vote_22
gen coalition_23=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace coalition_23=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 | vote_22==9 ///
						   | vote_22==12
replace coalition_23=3 if vote_22>=14 & vote_22<=16 
label define coal_lab1 1 "Coalition" 2 "Opposition" 3 "Other"
label values coalition_23 coal_lab1
tab vote_22 coalition_23
tab coalition_23 

* Ideological "blocs"
tab ideology
recode ideology (1/3=1) (4=2) (5/7=3) (8/100=4), gen(ideo_bloc)
label define blocs_lab1 1 "Right" 2 "Center" 3 "Left" 4 "Other" 
label values ideo_bloc blocs_lab1
tab ideology ideo_bloc
tab ideo_bloc



**************************
** Study 6 - April 2025 **
**************************

** Setting the working directory **
**<ADD DIRECTORY>>>

* Uploading the dataset
use "Study 6 data.dta", clear


* Age group
drop age_group
recode Age (18/29=1) (30/49=2) (50/69=3) (70/99=4), gen (age_group)
label define ageg2_lab 1 "18-29" 2 "30-49" 3 "50-69" 4 "70+"
label value age_group ageg2_lab
tab Age age_group
tab age_group

* Gender
tab gender

* Jewish
tab jewish

* College education
tab college_educ

* Religiosity
tab religiosity_all if jewish==1 

* Coalition
drop coalition_23
tab vote_22
gen coalition_23=1 if vote_22==1 | vote_22==3 | vote_22==5 | vote_22==6
replace coalition_23=2 if vote_22==2 | vote_22==4 | vote_22==7 | vote_22==8 | ///
						   vote_22==10 | vote_22==11 | vote_22==13 | vote_22==9 ///
						   | vote_22==12
replace coalition_23=3 if vote_22>=14 & vote_22<=16 
label define coal_lab1 1 "Coalition" 2 "Opposition" 3 "Other"
label values coalition_23 coal_lab1
tab vote_22 coalition_23
tab coalition_23 

* Ideological "blocs"
tab ideology
recode ideology (1/3=1) (4=2) (5/7=3) (8/100=4), gen(ideo_bloc)
label define blocs_lab1 1 "Right" 2 "Center" 3 "Left" 4 "Other" 
label values ideo_bloc blocs_lab1
tab ideology ideo_bloc
tab ideo_bloc
